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PopNx MCPMCP servers for people who use AI · explained in plain words

glovebox

by vpatel9202version 0.3.2i★ –iRuns on your computer
Registry nameio.github.vpatel9202/glovebox

Install

Overview

Description from the maker (original English)

Computer use for coding agents on macOS: JS scripts, accessibility diffs, background input.

PopNx MCP’s three pillars

These three are never merged into one score: opinions, measurements and popularity are different things.

What you can do with it

We have not written a plain-language summary for this one yet. Below are the facts we read from the registry.

  • Connection: Runs on your computer
  • Transport: stdio
  • Category: Developer tools

Install

Pick the AI app you use, then copy the settings.

Before you install

  • Basic checks: 1 of 1 passed
  • Runs on your computer with your user’s permissions (files, network, apps).
  • The registry lists no key to fill in.

You need

  • npmNode.js installed (for the npx command)

Which app do you use?

Pick your app above. We remember it, so next time the button says “Install in …”.

Open Claude Desktop → Settings → Developer → Edit Config, and paste this into claude_desktop_config.json

{
  "mcpServers": {
    "glovebox": {
      "command": "npx",
      "args": [
        "-y",
        "@vashp2029/glovebox",
        "mcp"
      ]
    }
  }
}

Run this in your terminal

claude mcp add glovebox -- npx -y @vashp2029/glovebox mcp

Open in Cursor

Or copy the settings yourself

Paste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json

{
  "mcpServers": {
    "glovebox": {
      "command": "npx",
      "args": [
        "-y",
        "@vashp2029/glovebox",
        "mcp"
      ]
    }
  }
}

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

Open in VS Code

Or copy the settings yourself

Paste into .vscode/mcp.json in your project

{
  "servers": {
    "glovebox": {
      "type": "stdio",
      "command": "npx",
      "args": [
        "-y",
        "@vashp2029/glovebox",
        "mcp"
      ]
    }
  }
}

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

This one runs on your computer, and ChatGPT can only connect to servers on the internet. Pick another app.

Your choice stays on this device in a cookie; no account needed.

These settings are generated from the maker’s registry entry. If the README says otherwise, follow the README.

What it can do

Runs on your computer; the tool list appears in your AI app after you install it.

Basic checksi

We check information anyone can see; we have not read the code. Checks that do not apply are left out of the count. · Checked Nov 8, 2026

  • ✓ Pass

    Maker matches the repo

    The registry name was verified with the GitHub account vpatel9202, which owns the repo

  • … Not checked yet

    Still maintained

    We have not read this repo from GitHub yet

  • … Not checked yet

    Has a licence

    We have not read this repo from GitHub yet

  • – Not applicable

    Endpoint responds

    This one runs on your computer; there is no internet endpoint

  • – Not applicable

    Sign-in with OAuth

    Runs on your computer and uses local settings instead

  • … Not checked yet

    No hidden instructions in tool descriptions

    Runs on your computer; we can only read tool lists from internet endpoints

Compared with others in Developer toolsi

  • More stars than 0% of the other 4919 servers in this category
  • Published to the registry more recently than 90% of the other 4919 servers in this category
  • Basic checks equal to or better than 100% of the other 4919 servers in this category

Compared with every active server in this category in the registry. Stars count only when the publisher owns the repo.

Common questions

Is glovebox safe?

It passed 1 of 1 applicable basic checks. We have not read the code. Before adding a key or token, see what access the server asks for and use a key with only the permissions you need.

What keys or codes does it need?

The registry does not list a required key, though some servers ask you to sign in on first use.

Does it run on my computer or in the cloud?

It runs on your computer. Your AI app starts it when needed, and data does not pass through the maker’s servers (unless it calls an online service itself).

Is it still maintained?

The GitHub repo last changed –, and the latest version (0.3.2) reached the registry 4 days ago.

Which apps can use it?

Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need Node.js on your computer.

What can I use instead?

In the same category: GitHub, Desktop Commander, Cloudflare MCP

Alternatives

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Reading a card:★ GitHub starsiThree pillars: reviews · checks · usageiUpdated = latest version published to the registryi

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README from the maker

Open the README

Copied from the maker’s repo as written. PopNx MCP has not reviewed or endorsed it. HTML, images and scripts are removed. Links lead off this site.

glovebox

Computer use for coding agents on macOS: one JavaScript call per step, accessibility diffs instead of screenshots, and your screen stays yours.

const calc = await gb.getApp("Calculator");

await calc.pressKey("Escape"); await calc.typeText("6*7="); await calc.getAXState();

Calculator — window 0 "Calculator" — image 460x816 — changes since last read (~ changed, + added): ~ 8 scroll area id=StandardInputView;value:42 ~ 9 text "Edit field" value="42"

On the next call, calc is still bound. An agent writes a few lines per step instead of making one tool call per click, and reads what changed instead of a fresh picture of the window.

  • A script per step, not a tool call per click. Bindings and helper functions persist across calls, so one call can click, type, loop, and read.
  • Diffs, not screenshots. The default read is the accessibility tree as text, and later reads show only changes. Screenshots and pixel clicks are there when the tree is empty (Citrix, canvases).
  • Background by default. Keys, clicks, drags, and scrolls reach the app while you keep working in another one. Your cursor stays put, and a drawn cursor shows what the agent is doing.

In an author-run test of six setups on 12 tasks (2 runs each), glovebox had the lowest total cost, $0.57 against $1.41 to $5.67, and the fewest round trips and the most passes.

What to know first: macOS only, tested on macOS 27 on Apple silicon. You need the Xcode command line tools to build a small helper app, and you grant it Accessibility and Screen Recording. Background input uses two private macOS calls, with a foreground fallback. Only Claude Code has been tested end to end. Despite the name, this is not a sandbox, and it is unrelated to glovebox-mcp.

Quickstart

Requires Node 20.10+ and the Xcode command line tools (xcode-select --install).

npm install -g @vashp2029/glovebox

glovebox signing --create # optional: macOS keeps the grants across helper rebuilds glovebox setup # builds the helper, walks through permissions glovebox doctor # every line should say ok glovebox smoke # a real end-to-end test on Calculator claude mcp add --scope user glovebox -- glovebox mcp

setup builds Glovebox Helper.app into ~/.glovebox/ and asks you to turn it on under System Settings > Privacy & Security > Accessibility and Screen & System Audio Recording. Input Monitoring is optional and only enables Escape-to-stop. The helper is its own app, so one grant covers every agent and terminal. signing --create makes a self-signed certificate in your login keychain that signs only the helper. Without it, macOS treats each rebuild as a new app; see the upgrade note.

Works with: Claude Code (tested end to end). Codex, Grok CLI, OpenCode, Gemini CLI, and Cursor have documented configs that have not been exercised. Any agent that can run shell commands can use glovebox run. See docs/agents.md.

Why not Claude Code's built-in computer use?

If it fits your setup, it is the easier choice: nothing to install, supported by Anthropic, and it keeps your terminal out of screenshots. glovebox is for the cases where it does not fit. From Anthropic's docs, checked 2026-11-03:

Claude Code built-inglovebox
Your other appsHidden while Claude worksStay visible; input goes to the target app in the background
Default readDownscaled screenshotAccessibility text diff
Who can use itPro, Max, or Ultra through claude.ai; not Team, Enterprise, Bedrock, Google Cloud, or FoundryAnyone; it never talks to a model or an account
Scripted runsNot in -p modeThe benchmark drives it unattended from a script; claude -p itself not yet tested
SessionsOne at a time, enforced by a lock fileNo global lock; named sessions run side by side
Remembering approvalsThis session onlyAllow for This Session or Always Allow
BrowsersView-onlyFull control once you approve the browser, which is more power and more risk

Claude Code's built-in tool was not in the benchmark below, so this table compares documented behavior, not measured results.

Benchmark

Twelve macOS tasks, six setups, two runs each, 2026-11-03. Same model (Claude Sonnet 5.5, medium effort), prompt, and agent loop for every setup; only the tool changes. Task prompts name no tool, and a separate check that doesn't use the tool under test decides each result.

SetupPassedRound tripsImages returnedCost at list price
glovebox24/2412821$0.57
Codex cua_repl, driven by Claude20/2416630$1.41
Anthropic toolset, run by glovebox22/24187179$1.65
agent-desktop22/2420422$2.32
open-computer-use21/24244385$2.76
Peekaboo20/24359183$5.67

Where glovebox did not win. It was not cheapest on finder-rename ($0.061 against $0.041 for Codex cua_repl). It did not have the fewest round trips on 3 of the 12 tasks, or the fastest time on 3 of the 12. On remote-desktop it took 36 seconds against 22 and 23 for two others.

How much to trust this:

  • I wrote the tasks and ran the test, on one Mac, in one sitting. Several tasks (bulk-entry, remote-desktop, coexistence) were designed around things glovebox set out to do.
  • With two runs per task, pass counts mean little: 24/24 against 20/24 is not statistically significant. The cost gap is the sturdier result, because it holds task by task: glovebox cost less than each other setup on at least 11 of 12 tasks.
  • The glovebox tested is the code released as 0.3.0. Result files say 0.2.0, because the version had not been bumped yet.
  • "Anthropic toolset" is Anthropic's API computer-use toolset, executed through glovebox's foreground route. It failed coexistence because of that route, so that result doesn't describe a shipping product. "Codex cua_repl" measures the tool shape under Claude, not Codex with its own model.
  • Peekaboo's first pass was rerun with foreground input allowed, which helped it. Its two bulk-entry failures were my $0.75 per-run budget cap stopping the run. agent-desktop ran through its CLI, not its MCP mode.

Method, per-task numbers, and raw results: bench/ and bench/results/v2/summary.md.

How it compares

Checked against each project's README and docs on 2026-11-03. "—" means I could not confirm it from those.

PlatformsActions per callState between callsDefault readDiffed readsBackground inputNeeds
gloveboxmacOSmany (one script)persistent JS sessionaccessibility textyesyesXcode CLT to build the helper
Claude Code built-inmacOS (CLI)——screenshot—no, hides other appsPro, Max, or Ultra
Codex computer usemacOS, Windowsmany (one script)persistent JS sessionaccessibility textyesyes on macOSChatGPT app and plugin
lcumacOS (Apple silicon), Linuxas Codex; it runs Codex's runtimeas Codexas Codexas Codex—ChatGPT app installed
agent-desktopmacOS, Windows, Linuxone per command, plus batchrefs tied to a snapshotaccessibility tree JSON—yesHomebrew or npm
PeekaboomacOS 15+one per commandelement IDs from a snapshotscreenshot or JSON UI map—yesHomebrew or npm
open-computer-usemacOS, Linux, Windowsone per MCP call; CLI has sequences—app state——npm
computer-use-mcpmacOS 14+one per callelement IDsscreenshot and tree per action—yesnotarized binary
cua-drivermacOS, Windows, Linux————yessee its docs

Pick something else if you need Windows or Linux (agent-desktop, cua-driver, lcu), a notarized binary with no build step (computer-use-mcp), or want OpenAI's actual runtime and already have the ChatGPT app (lcu).

Safety

The first time a session touches an app, you get a dialog: Allow for This Session, Always Allow, or Deny. Terminals, password managers, System Settings, and a few others are blocked unless you run glovebox allow ; the list is in SECURITY.md. A script that had to bring an app forward stops if you switch away. Scripts running in the background keep going while you use other apps, and Escape stops any script if you grant Input Monitoring. Every action is logged to ~/.glovebox/actions.log.

An approved app is approved for everything in it: allowing a browser lets the agent use every site you are signed in to. glovebox does not screen page content for prompt injection. Treat it like giving someone remote control of that app. Details: SECURITY.md.

Known issue: while a background app's pop-up menu is open, macOS sends your keystrokes to that app, so a word you type can land in it (details).

How it works

agent ──MCP stdio──▶ glovebox mcp ──▶ kernel (persistent JS session)

agent ──shell──▶ glovebox run ──▶ daemon ──▶ kernel │ ▼ Unix socket Glovebox Helper.app (Swift: AX, CGEvent, ScreenCaptureKit, approval dialogs)

Background input uses two private macOS (SkyLight) functions, looked up at runtime with a foreground fallback; glovebox doctor reports which route you have. Everything else is public API. No OpenAI, Anthropic, or other vendor binaries.

Status

PlatformStatus
macOSWorks. Built for macOS 14+; tested only on macOS 27 (Apple silicon).
WindowsPlanned (UI Automation). See roadmap.
LinuxPlanned (AT-SPI; Wayland limited). See roadmap.

Run for real, not mocked: glovebox smoke and smoke --full over MCP (batched steps, persistent bindings, diffs, pixel clicks, and background click, drag, and scroll with another app frontmost), and Claude Code attached through glovebox mcp. Full list: docs/testing.md.

The API in one screen

  • gb.getApp(name) launches or finds an app without stealing focus. gb.listApps().
  • app.getAXState() returns the accessibility tree as text; later reads are diffs. {frames: true} adds element boxes, {disableDiffing: true} the full tree.
  • app.getScreenshot() is the only way to get an image.
  • app.click(target), doubleClick, rightClick, scroll, drag, setValue, focus, selectText, performSecondaryAction.
  • app.pressKey("ctrl+a") uses xdotool names (super is Cmd). app.typeText("text\n").
  • `app.waitForChange(

Only the beginning is shown; read the rest in the repo

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